CoinGlass MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds valuable behavioral context beyond annotations: it specifies that data is 'relatively static and cached for 5 minutes' and provides concrete examples of different query patterns. While annotations already indicate read-only, open-world, idempotent, and non-destructive behavior, the description enhances understanding of data freshness and usage patterns without contradicting annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured: a clear purpose statement, important behavioral context about data caching, and specific examples showing different use cases. Every sentence adds value without redundancy, and the information is front-loaded with the most important details first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, comprehensive annotations (read-only, open-world, idempotent), 100% schema coverage, and the presence of an output schema, the description provides complete context. It covers purpose, behavioral characteristics, and usage examples, making it fully adequate for an AI agent to understand and use this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the input schema already fully documents both parameters. The description provides examples showing how parameters combine (e.g., action='pairs' with exchange='Binance'), which adds some practical context, but doesn't significantly expand on the schema's parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get static market metadata from CoinGlass' with specific resources (coins, trading pairs, exchanges). It distinguishes from siblings by focusing on static metadata rather than dynamic data like funding rates, price history, or on-chain metrics found in other tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: for static market metadata that's cached for 5 minutes. It includes examples showing different use cases. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools for dynamic data needs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.